The nurse COVID and historical epidemics literature repository: Development, description, and summary.
Ontology highlight
ABSTRACT: Background
During COVID-19, a Kaggle challenge was issued to data scientists to leverage text mining to provide high-level summaries of full-text articles in the COVID-19 Open Research Dataset (CORD-19) data set, a data set containing articles around COVID-19 and other epidemics. A question was asked: "What if nursing had something similar?"Purpose
Describe the development and function of the Nursing COVID and Historical Epidemic Literature and describe high-level summaries of abstracts within the repository.Method
Nurse-specific literature was abstracted from two data sets: CORD-19 and LitCOVID. LitCOVID is a data set containing the most up-to-date literature around COVID-19. Multiple text mining algorithms were utilized to provide summaries of the articles.Discussion
As of July 2020, the repository contains 760 articles. Summaries indicate the importance of psychological support for nurses and of high-impact rapid education.Conclusion
To our knowledge, this repository is the only repository specific for nursing that utilizes text mining to provide summaries.
SUBMITTER: Loresto FL
PROVIDER: S-EPMC7846882 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Acute ischemic stroke (AIS) is a life-threatening complication of coronavirus disease 2019 (COVID-19) infection. Increasing reports suggest an association between COVID-19 and AIS, although the underlying mechanism remains uncertain. We performed a systematic review to characterize the clinical characteristics, neuroimaging findings, and outcomes of AIS in COVID-19 patients. A literature search was performed in PubMed and Embase using a suitable keyword search strategy from 1st December 2019 to 29th May 2020. All studies reporting AIS occurrence in COVID-19 patients were included. A total of 39 studies comprising 135 patients were studied. The pooled incidence of AIS in COVID-19 patients from observational studies was 1.2% (54/4466) with a mean age of 63.4 ± 13.1 years. The mean duration of AIS from COVID-19 symptoms onset was 10 ± 8 days, and the mean NIHSS score was 19 ± 8. Laboratory investigations revealed an elevated mean D-dimer (9.2 ± 14.8 mg/L) and fibrinogen (5.8 ± 2.0 g/L). Antiphospholipid antibodies were detected in a significant number of cases. The majority of AIS neuroimaging patterns observed was large vessel thrombosis, embolism or stenosis (62.1%, 64/103), followed by multiple vascular territory (26.2%, 27/103). A high mortality rate was reported (38.0%, 49/129). We report the pooled incidence of AIS in COVID-19 patients to be 1.2%, with a high mortality rate. Elevated D-dimer, fibrinogen and the presence of antiphospholipid antibodies appear to be prominent in COVID-19 patients with concomitant AIS, but further mechanistic studies are required to elucidate their role in pathogenesis.
| S-EPMC7358286 | biostudies-literature
Project description:Model-based epidemiological assessment is useful to support decision-making at the beginning of an emerging Aedes-transmitted outbreak. However, early forecasts are generally unreliable as little information is available in the first few incidence data points. Here, we show how past Aedes-transmitted epidemics help improve these predictions. The approach was applied to the 2015-2017 Zika virus epidemics in three islands of the French West Indies, with historical data including other Aedes-transmitted diseases (chikungunya and Zika) in the same and other locations. Hierarchical models were used to build informative a priori distributions on the reproduction ratio and the reporting rates. The accuracy and sharpness of forecasts improved substantially when these a priori distributions were used in models for prediction. For example, early forecasts of final epidemic size obtained without historical information were 3.3 times too high on average (range: 0.2 to 5.8) with respect to the eventual size, but were far closer (1.1 times the real value on average, range: 0.4 to 1.5) using information on past CHIKV epidemics in the same places. Likewise, the 97.5% upper bound for maximal incidence was 15.3 times (range: 2.0 to 63.1) the actual peak incidence, and became much sharper at 2.4 times (range: 1.3 to 3.9) the actual peak incidence with informative a priori distributions. Improvements were more limited for the date of peak incidence and the total duration of the epidemic. The framework can adapt to all forecasting models at the early stages of emerging Aedes-transmitted outbreaks.
| S-EPMC6002135 | biostudies-literature
Project description:BackgroundHospital workers have been the most frequently and severely affected professional group during the COVID-19 pandemic, and have a big impact on transmission. In this context, innovative tools are required to measure the symptoms compatible with COVID-19, the spread of infection, and testing capabilities within hospitals in real time.ObjectiveWe aimed to develop and test an effective and user-friendly tool to identify and track symptoms compatible with COVID-19 in hospital workers.MethodsWe developed and pilot tested Hospital Epidemics Tracker (HEpiTracker), a newly designed app to track the spread of COVID-19 among hospital workers. Hospital staff in 9 hospital centers across 5 Spanish regions (Andalusia, Balearics, Catalonia, Galicia, and Madrid) were invited to download the app on their phones and to register their daily body temperature, COVID-19-compatible symptoms, and general health score, as well as any polymerase chain reaction and serological test results.ResultsA total of 477 hospital staff participated in the study between April 8 and June 2, 2020. Of note, both health-related (n=329) and non-health-related (n=148) professionals participated in the study; over two-thirds of participants (68.8%) were health workers (43.4% physicians and 25.4% nurses), while the proportion of non-health-related workers by center ranged from 40% to 85%. Most participants were female (n=323, 67.5%), with a mean age of 45.4 years (SD 10.6). Regarding smoking habits, 13.0% and 34.2% of participants were current or former smokers, respectively. The daily reporting of symptoms was highly variable across participating hospitals; although we observed a decline in adherence after an initial participation peak in some hospitals, other sites were characterized by low participation rates throughout the study period.ConclusionsHEpiTracker is an already available tool to monitor COVID-19 and other infectious diseases in hospital workers. This tool has already been tested in real conditions. HEpiTracker is available in Spanish, Portuguese, and English. It has the potential to become a customized asset to be used in future COVID-19 pandemic waves and other environments.Trial registrationClinicalTrials.gov NCT04326400; https://clinicaltrials.gov/ct2/show/NCT04326400.
| S-EPMC7511223 | biostudies-literature
Project description:Background?Bayesian evolutionary analysis (coalescent analysis) based on genetic sequences has been used to describe the origins and spread of rapidly mutating RNA viruses, such as influenza, Ebola, human immunodeficiency virus (HIV), and hepatitis C virus (HCV).Methods?Full-length subtype 1a and 3a sequences from early HCV infections from the International Collaborative of Incident HIV and Hepatitis C in Injecting Cohorts (InC3), as well as from public databases from a time window of 1977-2012, were used in a coalescent analysis with BEAST software to estimate the origin and progression of the HCV epidemics in Australia and North America. Convergent temporal trends were sought via independent epidemiological modeling.Results?The epidemic of subtype 3a had more recent origins (around 1950) than subtype 1a (around 1920) in both continents. In both modeling approaches and in both continents, the epidemics underwent exponential growth between 1955 and 1975, which then stabilized in the late 20th century.Conclusions?Historical events that fuelled the emergence and spread of injecting drug use, such as the advent of intravenous medical therapies and devices, and growth in the heroin trade, as well as population mixing during armed conflicts, were likely drivers for the cross-continental spread of the HCV epidemics.
| S-EPMC5079374 | biostudies-literature
Project description:Late 19th century epidemics of tuberculosis (TB) in Western Canadian First Nations resulted in peak TB mortality rates more than six times the highest rates recorded in Europe. Using a mathematical modeling approach and historical TB mortality time series, we investigate potential causes of high TB mortality and rapid epidemic decline in First Nations from 1885 to 1940. We explore two potential causes of dramatic epidemic dynamics observed in this setting: first, we explore effects of famine prior to 1900 on both TB and population dynamics. Malnutrition is recognized as an individual-level risk factor for TB progression and mortality; its population-level effects on TB epidemics have not been explored previously. Second, we explore effects of heterogeneity in susceptibility to TB in two ways: modeling heterogeneity in susceptibility to infection, and heterogeneity in risk of developing disease once infected. Our results indicate that models lacking famine-related changes in TB parameters or heterogeneity result in an implausibly poor fit to both the TB mortality time series and census data; the inclusion of these features allows for the characteristic decline and rise in population observed in First Nations during this time period and confers improved fits to TB mortality data.
| S-EPMC4586807 | biostudies-literature
Project description:We describe a data repository on heritable disorders of connective tissue (HDCT) assembled by the National Institutes of Health's National Institute on Aging (NIA) Intramural Research Program between 2001 and 2013. Participants included affected persons with a wide range of heritable connective tissue phenotypes, and unaffected family members. Elements include comprehensive history and physical examination, standardized laboratory data, physiologic measures and imaging, standardized patient-reported outcome measures, and an extensive linked biorepository. The NIA made a commitment to make the repository available to extramural investigators and deposited samples at Coriell Tissue Repository (N = 126) and GenTAC registry (N = 132). The clinical dataset was transferred to Penn State University College of Medicine Clinical and Translational Science Institute in 2016, and data elements inventoried. The consented cohort of 1,009 participants averaged 39 ± 18 years (mean ± SD, range 2-95) at consent; gender distribution is 71% F and 83% self-report Caucasian ethnicity. Diagnostic categories include Ehlers-Danlos syndrome (classical N = 50, hypermobile N = 99, vascular N = 101, rare types and unclassified N = 178), Marfan syndrome (N = 33), Stickler syndrome (N = 60), fibromuscular dysplasia (N = 135), Other HDCT (N = 72). Unaffected family members (N = 218) contributed DNA for the molecular archive only. We aim to develop further discrete data from unstructured elements, analyze multisymptom HDCT manifestations, encourage data use by other researchers and thereby better understand the complexity of these high-morbidity conditions and their multifaceted effects on affected persons.
| S-EPMC6467085 | biostudies-literature
Project description:INTRODUCTION:COVID-19 pandemic burst onto the international scene as a new disease not affecting patients uniformly; hence it has risen many questions yet to be clarified. The aim of this study was to outline the main issues that led tobacco smoking being discussed as a potential risk factor associated with COVID-19. METHODS:articles from MEDLINE and pre-prints published from January to April 2020 were identified. RESULTS:data from China showed that men had more severe outcomes of COVID-19 than women. Since smoking prevalence is very high among Chinese men in comparison to women, it was hypothesized that smoking could be a risk factor for poor prognosis. This was also supported by the higher prevalence of comorbidities, many of which are tobacco-related diseases, in patients with severe COVID-19, who were also more likely to have a smoking history. A meta-analysis confirmed these results reporting an OR=2.25 (95% CI: 1.49-3.39) for developing severe Covid-19 among patients with a smoking history. Some authors, noticing that reported smoking prevalence among hospitalized patients was substantially below smoking prevalence in the corresponding populations, speculated a protective role of nicotine. However, it is likely that low prevalence among hospitalized patients are partially due to many smokers misclassified as nonsmokers. Tobacco smoking seems to cause a dose-dependent upregulation of the angiotensin-converting- enzyme-2 (ACE2), the virus cellular entry receptor, which could explain the higher risk of severe COVID-19 in smokers. CONCLUSIONS:There is need for further independent studies to clarify the role of smoking on COVID-19 incidence, progression and mortality.
| S-EPMC7569632 | biostudies-literature
Project description:The recent outbreak of COVID-19 has generated an enormous amount of Big Data. To date, the COVID-19 Open Research Dataset (CORD-19), lists ∼130,000 articles from the WHO COVID-19 database, PubMed Central, medRxiv, and bioRxiv, as collected by Semantic Scholar. According to LitCovid (11 August 2020), ∼40,300 COVID19-related articles are currently listed in PubMed. It has been shown in clinical settings that the analysis of past research results and the mining of available data can provide novel opportunities for the successful application of currently approved therapeutics and their combinations for the treatment of conditions caused by a novel SARS-CoV-2 infection. As such, effective responses to the pandemic require the development of efficient applications, methods and algorithms for data navigation, text-mining, clustering, classification, analysis, and reasoning. Thus, our COVID19 Drug Repository represents a modular platform for drug data navigation and analysis, with an emphasis on COVID-19-related information currently being reported. The COVID19 Drug Repository enables users to focus on different levels of complexity, starting from general information about (FDA-) approved drugs, PubMed references, clinical trials, recipes as well as the descriptions of molecular mechanisms of drugs' action. Our COVID19 drug repository provide a most updated world-wide collection of drugs that has been repurposed for COVID19 treatments around the world.
| S-EPMC7778969 | biostudies-literature
Project description:BACKGROUND:Planning interventions to respond to cholera epidemics requires an understanding of the major transmission routes. Interrupting short-cycle (household, foodborne) transmission may require different approaches as compared long-cycle (environmentally-mediated/waterborne) transmission. However, differentiating the relative contribution of short- and long-cycle routes has remained difficult, and most cholera outbreak control efforts focus on interrupting long-cycle transmission. Here we use high-resolution epidemiological and municipal infrastructure data from a cholera outbreak in 1853 Copenhagen to explore the relative contribution of short- and long-cycle transmission routes during a major urban epidemic. METHODOLOGY/PRINCIPAL FINDINGS:We fit a spatially explicit time-series meta-population model to 6,552 physician-reported cholera cases from Copenhagen in 1853. We estimated the contribution of long-cycle waterborne transmission between neighborhoods using historical municipal water infrastructure data, fitting the force of infection from hydraulic flow, then comparing model performance. We found the epidemic was characterized by considerable transmission heterogeneity. Some neighborhoods acted as localized transmission hotspots, while other neighborhoods were less affected or important in driving the epidemic. We found little evidence to support long-cycle transmission between hydrologically-connected neighborhoods. Collectively, these findings suggest short-cycle transmission was significant. CONCLUSIONS/SIGNIFICANCE:Spatially targeted cholera interventions, such as reactive vaccination or sanitation/hygiene campaigns in hotspot neighborhoods, would likely have been more effective in this epidemic than control measures aimed at interrupting long-cycle transmission, such as improving municipal water quality. We recommend public health planners consider programs aimed at interrupting short-cycle transmission as essential tools in the cholera control arsenal.
| S-EPMC5720805 | biostudies-literature
Project description:ObjectivesThis work was designed to adapt Geographical Information System-based spatial analysis to the study of historical epidemics. We mapped "plague" deaths during three epidemics of the early 15th century, analyzed spatial distributions by applying the Kulldorff's method, and determined their relationships with the distribution of socio-professional categories in the city of Dijon.Materials and methodsOur study was based on a database including 50 annual tax registers (established from 1376 to 1447) indicating deaths and survivors among the heads of households, their home location, tax level and profession. The households of the deceased and survivors during 6 years with excess mortality were individually located on a georeferenced medieval map, established by taking advantage of the preserved geography of the historical center of Dijon. We searched for clusters of heads of households characterized by shared tax levels (high-tax payers, the upper decile; low-tax payers, the half charged at the minimum level) or professional activities and for clusters of differential mortality.ResultsHigh-tax payers were preferentially in the northern intramural part, as well as most wealthy or specialized professionals, whereas low-tax payers were preferentially in the southern part. During two epidemics, in 1400-1401 and 1428, areas of higher mortality were found in the northern part whereas areas of lower mortality were in the southern one. A high concentration of housing and the proximity to food stocks were common features of the most affected areas, creating suitable conditions for rats to pullulate. A third epidemic, lasting from 1438 to 1440 had a different and evolving geography: cases were initially concentrated around the southern gate, at the confluence of three rivers, they were then diffuse, and ended with residual foci of deaths in the northern suburb.ConclusionUsing a selected historical source, we designed an approach allowing spatial analysis of urban medieval epidemics. Our results fit with the view that the 1400-1401 epidemic was a Black Death recurrence. They suggest that this was also the case in 1428, whereas in 1438-1440 a different, possibly waterborne, disease was involved.
| S-EPMC4666600 | biostudies-literature